import torch
from exps.run66.net import ReversiNet

BOARD_SIZE = 15
model = ReversiNet().eval()
model.load_state_dict(torch.load('exps/run66/checkpoint0003.pth', map_location='cpu'))
for layer in model.resblocks[2:]:
    layer.fuse()

model = torch.jit.script(model)
torch.jit.save(model, 'data/gomoku_230305.pth')
